Adaptive QoS scheduling in a service-oriented grid environment

The use of grid technology and web services for resource sharing has received tremendous attention in recent years. The merging of these 2 technologies is able to provide additional multiple types of services and functionalities. However, the problem of scheduling services to meet quality of service (QoS) requirements remains challenging. This paper proposes an adaptive QoS (AQoS) scheduling algorithm for service-oriented grid environments. AQoS uses benchmarking and curve-fitting based on historical records to estimate job length. Job length and users' QoS requirements are then used to make scheduling decisions. AQoS is able to maximize service availability, reliability, and resource utilization while minimizing total service execution time. Experimental results show that AQoS outperforms MIN-MIN and MAX-MIN algorithms by 10%-30% in terms of makespan and 5%-20% in terms of reliability.

Adaptive QoS scheduling in a service-oriented grid environment

The use of grid technology and web services for resource sharing has received tremendous attention in recent years. The merging of these 2 technologies is able to provide additional multiple types of services and functionalities. However, the problem of scheduling services to meet quality of service (QoS) requirements remains challenging. This paper proposes an adaptive QoS (AQoS) scheduling algorithm for service-oriented grid environments. AQoS uses benchmarking and curve-fitting based on historical records to estimate job length. Job length and users' QoS requirements are then used to make scheduling decisions. AQoS is able to maximize service availability, reliability, and resource utilization while minimizing total service execution time. Experimental results show that AQoS outperforms MIN-MIN and MAX-MIN algorithms by 10%-30% in terms of makespan and 5%-20% in terms of reliability.

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  • M. Mansukhani, Service Oriented Architecture White Paper, Palo Alto, CA, USA, Hewlett-Packard, 2005.
  • Y. Tang, Y. Yang, M. Zhao, L. Yao, Y. Li, “CoS-based QoS management framework for grid services”, Sixth International Conference on Grid and Cooperative Computing, pp. 451-455, 2007.
  • F. Dong, S.G. Akl, Scheduling Algorithms for Grid Computing: State of the Art and Open Problems, Technical Report 2006-504, School of Computing, Queen’s University, Ontario, Canada, 2006.
  • Y.C. Lee, A.Y. Zomaya, “Practical scheduling of bag-of-tasks applications on grids with dynamic resilience”, IEEE Transactions on Computers, Vol. 56, pp. 815-825, 2007.
  • N.D. Doulamis, A.D. Doulamis, E.A. Varvarigos, T.A. Varvarigou, “Fair scheduling algorithms in grids”, IEEE Transactions on Parallel and Distributed Systems, Vol. 18, pp. 1630-1648, 2007.
  • K. Etminani, M. Naghibzadeh, “A min-min max-min selective algorithm for grid task scheduling”, IEEE/IFIP International Conference in Central Asia on Internet, pp. 1-7, 2007.
  • C. Du, X.H. Sun, M. Wu, “Dynamic scheduling with process migration”, International Symposium on Cluster Computing and the Grid, pp. 92-99, 2007.
  • T.F. Ang, W.K. Ng, T.C. Ling, L.Y. Por, C.S. Liew, “A bandwidth-aware job grouping-based scheduling on grid environment”, Information Technology Journal, Vol. 8, pp. 372-377, 2009.
  • J.K. Kim, S. Shivle, H.J. Siegel, A.A. Maciejewski, T.D. Braun, M. Schneider, S. Tideman, R. Chitta, R.B. Dilmaghani, R. Joshi, A. Kaul, A. Sharma, S. Sripada, P. Vangari, S.S. Yellampalli, “Dynamically mapping tasks with priorities and multiple deadlines in a heterogeneous environment”, Journal of Parallel and Distributed Computing, Vol. 67, pp. 154-169, 2007.
  • N. Muthuvelu, I. Chai, C. Eswaran, “An adaptive and parameterized job grouping algorithm for scheduling grid jobs”, 10th International Conference on Advanced Communication Technology, pp. 975-980, 2008.
  • T. Braun, H. Siegel, N. Beck, L. Boloni, M. Maheswaran, A. Reuther, J. Robertson, M. Theys, B. Yao, “A comparison of eleven static heuristics for mapping a class of independent tasks onto heterogeneous distributed computing systems”, Journal of Parallel and Distributed Computing, Vol. 61, pp. 810-837, 2001.
  • E. Caron, V. Garonne, A. Tsaregorodtsev, “DeŞnition, modelling and simulation of a grid computing scheduling system for high throughput computing”, Future Generation Computer Systems, Vol. 23, pp. 968-976, 2007.
  • X.S. He, X.H. Sun, G. von Laszewski, “QoS guided min-min heuristic for grid task scheduling”, Journal of Computer Science and Technology, Vol. 18, pp. 442-451, 2003.
  • C. Hu, M. Wu, G. Liu, W. Xie, “QoS scheduling algorithm based on hybrid particle swarm optimization strategy for grid workflow”, Sixth International Conference on Grid and Cooperative Computing, pp. 330-337, 2007.
  • P.C. Xiong, Y.S. Fan, M.C. Zhou, “QoS-aware web service conŞguration”, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 38, pp. 888-895, 2008.
  • P.C. Xiong, Y.S. Fan, M.C. Zhou, “Web service conŞguration under multiple quality-of-service attributes”, IEEE Transactions on Automation Science and Engineering, Vol. 6, pp. 311-321, 2009.
  • M. Wahib, A. Munawar, M. Munetomo, A. Kiyoshi, “SOAG: Service oriented architectured grids and adoption of application speciŞc QoS attributes”, IEEE Grid Computing Conference, pp. 346-351, 2008.
  • L. Guo, A.S. McGough, A. Akram, D. Colling, J. Martyniak, M. Krznaric, “Enabling QoS for service-oriented workflow on GRID”, International Conference on Computer and Information Technology, pp. 1077-1082, 2007.
  • Q.Z. Sheng, B. Benatallah, Z. Maamar, A.H.H. Ngu, “ConŞgurable composition and adaptive provisioning of web services”, IEEE Transactions on Service Computing, Vol. 2, pp. 34-49, 2009.
  • A. Filali, A.S. HaŞd, M. Gendreau, “Adaptive resources provisioning for grid applications and services”, IEEE International Conference on Communications, pp. 186-191, 2008.
  • C.C. Lo, D.Y. Cheng, P.C. Lin, K.M. Chao, “A study on representation of QoS in UDDI for web services composition”, International Conference on Complex, Intelligent and Software Intensive Systems, pp. 423-428, 2008.
  • C.P. Gavald`a, P.G. L´opez, R.M. Andreu, “Deploying wide-area applications is a snap”, IEEE Internet Computing, Vol. 11, pp. 72-79, 2007.
  • D. Lazaro, J.M. Marques, J. Jorba, “An architecture for decentralized service deployment”, International Conference on Complex, Intelligent and Software Intensive Systems, pp. 327-332, 2008.
  • G. Kecskemeti, P. Kacsuk, G. Terstyanszky, T. Kiss, T. Delaitre, “Automatic service deployment using virtualisa- tion”, 16th Euromicro Conference on Parallel, Distributed and Network-Based Processing, pp. 628-635, 2008.
  • B. House, P. Marshall, M. Oberg, H.M. Tufo, “Grid service hosting on virtual clusters”, Proceedings of the 9th IEEE/ACM International Conference on Grid Computing, pp. 304-309, 2008.
  • L. Wang, G. von Laszewski, J. Tao, M. Kunze, “Grid virtualization engine: design, implementation, and evaluation”, IEEE Systems Journal, Vol. 3, pp. 477-488, 2009. PassMark, PassMark Software , Sydney, Australia,
  • PassMark r Software Pty Ltd. Available at http://www.cpubenchmark.net/. A.T. Fong, L.T. Chaw, P.K. Keong, P.L. Yee, “Automatic web services deployment”, World Congress on Computer Science and Information Engineering, pp. 315-319, 2009.